Self regulation and race/ethnic disparities in school readiness: Kindergarten Follow Up although the importance of behavioral self regulation skills for school readiness is widely accepted, little is known about the development of these skills among low income African American and Latino children. These children are significantly more likely to experience early academic failure, and deficits in early achievement have long-term implications, including greater risk of high school dropout and poor health. Further, no studies have examined the combined impact of both of a supportive home environment and a supportive kindergarten classroom on emerging self regulation and early academic performance among minority children. This study builds upon an ARRA-funded project that established a cohort of 404 low income Latino (predominantly Mexican American) and African American children who were originally enrolled at 21/2 years of age. The proposed project will follow the sample into kindergarten and first grade to examine the relation of individual differences in self regulation development to differences in early academic performance. We will address the following specific aims in this sample of low income Latino and African American children: Aim 1. Examine how individual differences in the emergence of behavioral self regulation are related to differences in academic performance in kindergarten and first grade. Aim 2. Identify how family-level risk and protective factors contribute to the emergence of behavioral self regulation and academic performance in kindergarten and first grade. Aim 3. Examine how the kindergarten classroom environment contributes to the development of self regulation as well as moderates the relation between self regulation and academic performance in kindergarten and first grade. Data collection methods will include home visits and teacher interviews. Measures include child self regulation tasks, assessments of academic performance and social competence, family environment, classroom environment, teacher-child relationship, and child behavior in the classroom. Analytic methods will include multiple linear regression, structural equations modeling, and latent growth curve analysis.